Angelo Iezzi

Validity and Reliability of the Assessment of Quality of Life (AQoL)-8D Multi-Attribute Utility Instrument

ObjectiveThe purpose of this paper was to report tests of the validity and reliability of a new instrument, the Assessment of Quality of Life (AQoL)-8D, which was constructed to improve the evaluation of health services that have an impact upon the psychosocial aspects of the quality of life.MethodsAustralian and US data from a large multi-instrument comparison survey were used to conduct tests of convergent, predictive and content validity using as comparators five other multi-attribute utility (MAU) instruments—the EQ-5D, SF-6D, Health Utilities Index (HUI) 3, 15D and the Quality of Well-Being (QWB)—as well as four non-utility instruments—the SF-36 and three measures of subjective well-being (SWB). A separate three part Australian survey was used to assess test–retest reliability.ResultsResults indicate that AQoL-8D correlates more highly with both the SWB instruments and the psychosocial dimensions of the SF-36, and that it is similar to the other MAU instruments in terms of its convergent and predictive validity. The second Australian survey demonstrated high test–retest reliability.ConclusionsThe results indicate that the AQoL-8D is a reliable and valid instrument which offers an alternative to the MAU instruments presently used in economic evaluation studies, and one which is particularly suitable when psychosocial elements of health are of importance.

Comparing and Explaining Differences in the Magnitude, Content, and Sensitivity of Utilities Predicted by the EQ-5D, SF-6D, HUI 3, 15D, QWB, and AQoL-8D Multiattribute Utility Instruments

Background. Cost utility analysis permits the comparison of disparate health services by measuring outcomes in comparable units, namely, quality-adjusted life-years, which equal life-years times the utility of the health state. However, comparability is compromised when different utility instruments predict different utilities for the same health state. The present paper measures the extent of, and reason for, differences between the utilities predicted by the EQ-5D-5L, SF-6D, HUI 3, 15D, QWB, and AQoL-8D. Methods. Data were obtained from patients in seven disease areas and members of the healthy public in six countries. Differences between public and patient utilities were estimated using each of the instruments. To explain discrepancies between the estimates, the measurement scales and content of the instruments were compared. The sensitivity of instruments to independently measured health dimensions was measured in pairwise comparisons of all combinations of the instruments. Results. The difference between public and patient utilities varied with the choice of instrument by more than 50% for every disease group and in four of the seven groups by more than 100%. Discrepancies were associated with differences in both the instrument content and their measurement scales. Pairwise comparisons of instruments found that variation in the sensitivity to physical and psychosocial dimensions of health closely reflected the items in the instruments descriptive systems. Discussion. Results indicate that instruments measure related but different constructs. They imply that commonly used instruments systematically discriminate against some classes of services, most notably mental health services. Differences in the instrument scales imply the need for transformations between the instruments to increase the comparability of measurement.

Construction of the descriptive system for the assessment of quality of life AQoL-6D utility instrument

BackgroundMulti attribute utility (MAU) instruments are used to include the health related quality of life (HRQoL) in economic evaluations of health programs. Comparative studies suggest different MAU instruments measure related but different constructs. The objective of this paper is to describe the methods employed to achieve content validity in the descriptive system of the Assessment of Quality of Life (AQoL)-6D, MAU instrument.MethodsThe AQoL program introduced the use of psychometric methods in the construction of health related MAU instruments. To develop the AQoL-6D we selected 112 items from previous research, focus groups and expert judgment and administered them to 316 members of the public and 302 hospital patients. The search for content validity across a broad spectrum of health states required both formative and reflective modelling. We employed Exploratory Factor Analysis and Structural Equation Modelling (SEM) to meet these dual requirements.Results and DiscussionThe resulting instrument employs 20 items in a multi-tier descriptive system. Latent dimension variables achieve sensitive descriptions of 6 dimensions which, in turn, combine to form a single latent QoL variable. Diagnostic statistics from the SEM analysis are exceptionally good and confirm the hypothesised structure of the model.ConclusionsThe AQoL-6D descriptive system has good psychometric properties. They imply that the instrument has achieved construct validity and provides a sensitive description of HRQoL. This means that it may be used with confidence for measuring health related quality of life and that it is a suitable basis for modelling utilities for inclusion in the economic evaluation of health programs.

Vision and Quality of Life: Development of Methods for the VisQoL Vision-Related Utility Instrument

Purpose: To describe the methods and innovations used in constructing the VisQoL, a vision-related utility instrument for the health economic evaluation of eye care and rehabilitation programs. Methods: The VisQoL disaggregates vision into six items. Utilities were estimated for item worst responses (the worst level for each item, with all other items at their best level) and VisQoL all-worst responses (all items at their worst level) using the time trade-off procedure. Time trade-off questions require people to imagine living a fixed number of years with a particular health condition and then indicate how many of those years of life they would be willing to trade to have perfect health. Where respondents indicated a health state was “worse than death” negative utilities were estimated. Time trade-off questions minimized the “focusing effect,” which occurs if respondents discount the fact that all other aspects of health are at their best when answering questions, by using pictorial and verbal aids. Results: Item utilities were combined using a multiplicative model, and VisQoL model utilities placed on a scale where 0.00 and 1.00 represent full health and death, respectively. The VisQoL allows utilities to be calculated for a wide range of vision-related conditions. Conclusion: The 6-item VisQoL has excellent psychometric properties and is specifically designed to be sensitive to vision-related quality of life. It is the first instrument to permit the rapid estimation of utility values for use in economic evaluations of vision-related programs.

Modelling utility weights for the Assessment of Quality of Life (AQoL)-8D

AbstractPurposeThe objective of this paper is to describe the four-stage methodology used to obtain utility scores for the Assessment of Quality of Life (AQoL)-8D, a 35-item 8 dimension multi-attribute utility instrument, which was created to achieve a high degree of sensitivity to psycho-social health.MethodsData for the analyses were obtained from a representative group of 347 members of the Australian public and from 323 mental health patients each of whom provided VAS and time trade-off valuations of multiple health states. Data were used initially to create multiplicative scoring algorithms for each of the instrument’s 8 dimensions and for the overall instrument. Each of the algorithms was then subject to a second-stage econometric ‘correction’.ResultsAlgorithms were successfully created for each of the AQoL-8D’s dimensions, for physical and mental ‘super-dimensions’ and for the overall AQoL-8D instrument. The final AQoL-8D algorithm has good predictive power with respect to the TTO valuations.ConclusionsThe AQoL-8D is a suitable instrument for researchers conducting cost utility analyses generally but, in particular, for the analysis of services affecting psycho-social health.

Severity as an independent determinant of the social Value of a health service

This paper has two objectives, first to review the relevant literature concerning the social importance of severity of pre-treatment condition, and second to present the results of a new analysis of the relationship between social value, individual assessment of health improvement and the severity of illness. The present study differs methodologically from others reported in the literature. The underlying hypothesis is that members of the public have an aversion to patients being in a severe health state irrespective of the reason for their being there, and that this aversion will affect the social valuation of a health program after taking account of the magnitude of the health improvement. This effect will be observable in a program which (compared to another) takes a person out of a severe health state—the usual case discussed in the literature—or in a program which (compared to another) leaves a person in a severe health state. The present study tests this second implication of the hypothesis. We present data consistent with the view that after taking account of health improvement, health programs are preferred which do not leave people in severe health states. Alternative explanations are considered and particularly the possibility that data reflect a social preference for individuals achieving their health potential. Both explanations imply the need to reconsider the rules for prioritising programs. In this analysis, Person Trade-Off (PTO) scores are used to measure social preferences (‘value’ or ‘social utility’) and Time Trade-Off (TTO) scores are used to measure individual assessments of health improvement and initial severity. Econometric results suggest that severity is highly significant and may more than double the index of social value of a health service.

Measuring the Sensitivity and Construct Validity of 6 Utility Instruments in 7 Disease Areas

Background. Health services that affect quality of life (QoL) are increasingly evaluated using cost utility analyses (CUA). These commonly employ one of a small number of multiattribute utility instruments (MAUI) to assess the effects of the health service on utility. However, the MAUI differ significantly, and the choice of instrument may alter the outcome of an evaluation. Aims. The present article has 2 objectives: 1) to compare the results of 3 measures of the sensitivity of 6 MAUI and the results of 6 tests of construct validity in 7 disease areas and 2) to rank the MAUI by each of the test results in each disease area and by an overall composite index constructed from the tests. Methods. Patients and the general public were administered a battery of instruments, which included the 6 MAUI, disease-specific QoL instruments (DSI), and 6 other comparator instruments. In each disease area, instrument sensitivity was measured 3 ways: by the unadjusted mean difference in utility between public and patient groups, by the value of the effect size, and by the correlation between MAUI and DSI scores. Content and convergent validity were tested by comparison of MAUI utilities and scores from the 6 comparator instruments. These included 2 measures of health state preferences, measures of subjective well-being and capabilities, and generic measures of physical and mental QoL derived from the SF-36. Results. The apparent sensitivity of instruments varied significantly with the measurement method and by disease area. Validation test results varied with the comparator instruments. Notwithstanding this variability, the 15D, AQoL-8D, and the SF-6D generally achieved better test results than the QWB and EQ-5D-5L.

Mapping between 6 Multiattribute Utility Instruments

Background: Cost-utility analyses commonly employ a multiattribute utility (MAU) instrument to estimate the health state utilities, which are needed to calculate quality-adjusted life years. Different MAU instruments predict significantly different utilities, which makes comparison of results from different evaluation studies problematical. Aim: This article presents mapping functions (“crosswalks”) from 6 MAU instruments (EQ-5D-5L, SF-6D, Health Utilities Index 3 [HUI 3], 15D, Quality of Well-Being [QWB], and Assessment of Quality of Life 8D [AQoL-8D]) to each of the other 5 instruments in the study: a total of 30 mapping functions. Methods: Data were obtained from a multi-instrument comparison survey of the public and patients in 7 disease areas conducted in 6 countries (Australia, Canada, Germany, Norway, United Kingdom, and United States). The 8022 respondents were administered each of the 6 study instruments. Mapping equations between each instrument pair were estimated using 4 econometric techniques: ordinary least squares, generalized linear model, censored least absolute deviations, and, for the first time, a robust MM-estimator. Results: Goodness-of-fit indicators for each of the results are within the range of published studies. Transformations reduced discrepancies between predicted utilities. Incremental utilities, which determine the value of quality-related health benefits, are almost perfectly aligned at the sample means. Conclusion: Transformations presented here align the measurement scales of MAU instruments. Their use will increase confidence in the comparability of evaluation studies, which have employed different MAU instruments.

Do quality-adjusted life years take account of lost income? Evidence from an Australian survey

The procedures used in cost utility analysis for eliciting quality of life weights have generally omitted any instruction concerning the level of consumption in a health state, despite the fact that some health states preclude the possibility of normal employment. This introduces ambiguity into the interpretation of quality of life (QoL) scores, and project ranking is sensitive to the subsequent treatment of consumption in the analysis. This article reports the results of a study that questioned 131 respondents to a time trade-off (TTO) interview about their assumptions concerning consumption and the amount of thought given to consumption. Results indicate that, without prompting, most assumed unchanged consumption, implying little bias in existing studies.

Can multi-attribute utility instruments adequately account for subjective well-being?

Introduction: The quality of life is included in cost utility analyses by weighting the relevant years of life by health state utilities. However, the utilities predicted by multi-attribute utility instruments (MAUIs) for this purpose do not correlate highly with the subjective well-being (SWB) of people experiencing the health states. This suggests that MAUIs may not take account of the SWB experienced by patients. This article explores an alternative hypothesis: that a failure of an MAUI to account for variation in SWB is primarily a result of the failure of its descriptive system to include the elements of health that determine SWB and that cannot therefore be included in assessment of the health state utility. Methods: Survey data are used to determine the extent to which 6 MAUIs with significantly different descriptive systems explain differences between the SWB of the healthy public and patients in 7 disease areas. Results: The EQ-5D-5L takes least account and AQoL-8D most account of SWB. AQoL-8D overpredicts the loss of SWB in 2 cases where hedonic adaptation is known to occur. Discussion: Results suggest that, to a large extent, utility can account for variation in SWB. The case for replacing utility with SWB in economic evaluation studies has arisen, in part, because elements of importance for SWB have been omitted from the descriptive systems of commonly used MAUIs.